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Showing 3 results for Subject:
Mojtaba Moradi,
Volume 11, Issue 2 (3-2018)
Abstract
The basic reproduction number is the average number of secondary infection cases generated by a single primary case in a susceptible population. Estimation of the basic reproduction number is important in medical studies. In this paper, we describe a new method for estimating the basic reproduction number by branching processes. Finally, we apply this estimator on real data reported by the National Center for Biotechnology Information in the USA.
Reza Zarei, ,
Volume 14, Issue 2 (2-2021)
Abstract
In this paper, the Bayesian and empirical Bayesian approaches studied in estimate the multicomponent stress–strength reliability model when the strength and stress variables have a generalized Rayleigh distribution with different shape parameters and identical scale parameter. The Bayesian, empirical Bayesian and maximum likelihood estimation of reliability function is obtained in the two cases known and unknown of scale parameter under the mean squared error loss function. Then, these estimators are compared empirically using Monte Carlo simulation and two real data sets.
Elham Ranjbar, Mohamad Ghasem Akbari, Reza Zarei,
Volume 19, Issue 1 (9-2025)
Abstract
In the time series analysis, we may encounter situations where some elements of the model are imprecise quantities. One of the most common situations is the inaccuracy of the underlying observations, usually due to measurement or human errors. In this paper, a new fuzzy autoregressive time series model based on the support vector machine approach is proposed. For this purpose, the kernel function has been used for the stability and flexibility of the model, and the constraints included in the model have been used to control the points. In order to examine the performance and effectiveness of the proposed fuzzy autoregressive time series model, some goodness of fit criteria are used. The results were based on one example of simulated fuzzy time series data and two real examples, which showed that the proposed method performed better than other existing methods.
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